Use web scraping and NLP to find the most frequent words in Herman Melville's novel, Moby Dick.
In this Project, you'll scrape the novel Moby Dick from the website Project Gutenberg
(which contains a large corpus of books) using the Python package
Then you'll extract words from this web data using BeautifulSoup.
Finally, we'll dive into analyzing the distribution of words using
the Natural Language ToolKit (
nltk). The natural language processing tools
used here apply to much of the data that data scientists encounter as a vast
proportion of the world's data is unstructured data and includes a great deal of text.
To complete this Project, you need to know how to import web data into python and how to work with natural language text. Before starting this project we recommend that you have completed the following courses:
This Project is based on a live screencast by DataCamp's own Hugo Bowne-Anderson. When you've finished the Project, or if you get stuck, do check out the screencast with Hugo's solution (the screencast starts 12 minutes into the video). You can also find Hugo's solution notebook here.
Data Scientist at DataCamp
Hugo is a data scientist, educator, writer and podcaster and DataCamp. His main interests are promoting data & AI literacy, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. If you want to know what he likes to talk about, definitely check out DataFramed, the DataCamp podcast, which he hosts and produces: https://www.datacamp.com/community/podcastSee More